<!DOCTYPE html>
<!--

	Modified template for STM32CubeMX.AI purpose

	d0.1: 	jean-michel.delorme@st.com
			add ST logo and ST footer

	d2.0: 	jean-michel.delorme@st.com
			add sidenav support

	d2.1: 	jean-michel.delorme@st.com
			clean-up + optional ai_logo/ai meta data
			
==============================================================================
           "GitHub HTML5 Pandoc Template" v2.1 — by Tristano Ajmone           
==============================================================================
Copyright © Tristano Ajmone, 2017, MIT License (MIT). Project's home:

- https://github.com/tajmone/pandoc-goodies

The CSS in this template reuses source code taken from the following projects:

- GitHub Markdown CSS: Copyright © Sindre Sorhus, MIT License (MIT):
  https://github.com/sindresorhus/github-markdown-css

- Primer CSS: Copyright © 2016-2017 GitHub Inc., MIT License (MIT):
  http://primercss.io/

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The MIT License 

Copyright (c) Tristano Ajmone, 2017 (github.com/tajmone/pandoc-goodies)
Copyright (c) Sindre Sorhus <sindresorhus@gmail.com> (sindresorhus.com)
Copyright (c) 2017 GitHub Inc.

"GitHub Pandoc HTML5 Template" is Copyright (c) Tristano Ajmone, 2017, released
under the MIT License (MIT); it contains readaptations of substantial portions
of the following third party softwares:

(1) "GitHub Markdown CSS", Copyright (c) Sindre Sorhus, MIT License (MIT).
(2) "Primer CSS", Copyright (c) 2016 GitHub Inc., MIT License (MIT).

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
==============================================================================-->
<html>
<head>
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  <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" />
  <title>Keras stateful LSTM support</title>
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										<br />7.0.0-dev<br />
										<a href="#doc_title"> Keras stateful LSTM support </a>
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		<ul>
  <li><a href="#introduction">Introduction</a></li>
  <li><a href="#state-buffer-allocation">State buffer allocation</a></li>
  <li><a href="#validate-command-limitation">Validate command limitation</a></li>
  <li><a href="#references">References</a></li>
  <li><a href="#revision-history">Revision history</a></li>
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<section class="st_header" id="doc_title">

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<h1 class="title followed-by-subtitle">Keras stateful LSTM support</h1>

	<p class="subtitle">X-CUBE-AI Expansion Package</p>

	<div class="revision">r1.0</div>

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		AI PLATFORM r7.0.0-dev
					(Embedded Inference Client API 1.1.0)
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			Command Line Interface r1.4.2
	




</section>
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<section id="introduction" class="level1">
<h1>Introduction</h1>
<p>X-CUBE-AI v6 provides an initial support for the Keras stateful LSTM. Only a <code>batch-size</code> of <code>1</code> is supported and to manage completely the state of the layer, a weak function should be provided by the client application. <code>return-state</code> is also not supported.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>inputs <span class="op">=</span> tf.keras.layers.Input(shape<span class="op">=</span>(<span class="dv">1</span>, <span class="dv">64</span>), batch_size<span class="op">=</span><span class="dv">1</span>)</span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a>lstm <span class="op">=</span> tf.keras.layers.LSTM(<span class="dv">20</span>, activation<span class="op">=</span><span class="st">&#39;relu&#39;</span>, stateful<span class="op">=</span><span class="va">True</span>,</span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a>                                return_sequences<span class="op">=</span><span class="va">True</span>)(inputs)</span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a>dense <span class="op">=</span> tf.keras.layers.Dense(<span class="dv">5</span>)(lstm)</span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a>model <span class="op">=</span> tf.keras.Model([inputs], [dense])</span></code></pre></div>
</section>
<section id="state-buffer-allocation" class="level1">
<h1>State buffer allocation</h1>
<p>By default, a weak function is implemented in the network runtime library. It is called during the execution of the <a href="embedded_client_api.html#ref_api_init"><code>ai_&lt;network&gt;_init()</code></a> function. Allocated in the system heap, the state buffer will be used by the forward LSTM function during the inference (<code>ai_&lt;network&gt;_run()</code> function) to restore and to save the global state.</p>
<ul>
<li>called for each instance of the Keras stateful LSTM layer<br />
</li>
<li><code>size_in_bytes = 2 * n_cell * sizeof(ai_float)</code></li>
</ul>
<div class="sourceCode" id="cb2"><pre class="sourceCode c"><code class="sourceCode c"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>AI_DECLARE_WEAK</span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="dt">void</span> _allocate_lstm_states<span class="op">(</span>ai_float <span class="op">**</span>states<span class="op">,</span> ai_u32 size_in_bytes<span class="op">)</span></span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a><span class="op">{</span></span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a>  ai_handle src <span class="op">=</span> AI_HANDLE_PTR<span class="op">(*</span>states<span class="op">);</span></span>
<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a>  <span class="op">*</span>states <span class="op">=</span> <span class="op">(</span>ai_float<span class="op">*)</span>realloc<span class="op">(</span>src<span class="op">,</span> size_in_bytes<span class="op">);</span></span>
<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a>  <span class="co">// Clear lstm initial state</span></span>
<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a>  <span class="cf">if</span> <span class="op">(*</span>states<span class="op">)</span> <span class="op">{</span></span>
<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a>    memset<span class="op">(*</span>states<span class="op">,</span> <span class="dv">0</span><span class="op">,</span> size_in_bytes<span class="op">);</span></span>
<span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a>  <span class="op">}</span></span>
<span id="cb2-10"><a href="#cb2-10" aria-hidden="true" tabindex="-1"></a><span class="op">}</span></span></code></pre></div>
<p>As illustrated in the following snippet code, to be able to set the state at a specific value or to reset the state regularly, this function should be implemented by the client application to have a reference on the allocated buffers.</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode c"><code class="sourceCode c"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="dt">static</span> ai_float<span class="op">*</span> _lstm_states<span class="op">[</span>NUM_INSTANCES<span class="op">]</span> <span class="op">=</span> <span class="op">{};</span></span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a><span class="dt">static</span> ai_u32 _lstm_states_size<span class="op">[</span>NUM_INSTANCES<span class="op">]</span> <span class="op">=</span> <span class="op">{};</span></span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a><span class="dt">static</span> <span class="dt">int</span> _lstm_instance_idx <span class="op">=</span> <span class="dv">0</span><span class="op">;</span></span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a><span class="dt">void</span> _allocate_lstm_states<span class="op">(</span>ai_float <span class="op">**</span>states<span class="op">,</span> ai_u32 size_in_bytes<span class="op">)</span></span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a><span class="op">{</span></span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a>  <span class="cf">if</span> <span class="op">((</span>_lstm_instance_idx <span class="op">&gt;</span> NUM_INSTANCES<span class="op">)</span> <span class="op">||</span> <span class="op">(!</span>states<span class="op">)</span> <span class="op">||</span> <span class="op">(*</span>states<span class="op">)</span> <span class="op">||</span> <span class="op">(!</span>size_in_bytes<span class="op">))</span> <span class="op">{</span></span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a>      <span class="co">/* error - invalid call */</span></span>
<span id="cb3-9"><a href="#cb3-9" aria-hidden="true" tabindex="-1"></a>      <span class="cf">return</span><span class="op">;</span></span>
<span id="cb3-10"><a href="#cb3-10" aria-hidden="true" tabindex="-1"></a>  <span class="op">}</span></span>
<span id="cb3-11"><a href="#cb3-11" aria-hidden="true" tabindex="-1"></a>  ai_handle src <span class="op">=</span> AI_HANDLE_PTR<span class="op">(*</span>states<span class="op">);</span></span>
<span id="cb3-12"><a href="#cb3-12" aria-hidden="true" tabindex="-1"></a>  _lstm_states<span class="op">[</span>_lstm_instance_idx<span class="op">]</span> <span class="op">=</span> <span class="op">(</span>ai_float <span class="op">*)</span>malloc<span class="op">(</span>size_in_bytes<span class="op">);</span></span>
<span id="cb3-13"><a href="#cb3-13" aria-hidden="true" tabindex="-1"></a>  _lstm_states_size<span class="op">[</span>_lstm_instance_idx<span class="op">]</span> <span class="op">=</span> size_in_bytes<span class="op">;</span></span>
<span id="cb3-14"><a href="#cb3-14" aria-hidden="true" tabindex="-1"></a>  <span class="op">*</span>states <span class="op">=</span> _lstm_states<span class="op">[</span>_lstm_instance_idx<span class="op">];</span></span>
<span id="cb3-15"><a href="#cb3-15" aria-hidden="true" tabindex="-1"></a>  <span class="co">/* </span></span>
<span id="cb3-16"><a href="#cb3-16" aria-hidden="true" tabindex="-1"></a><span class="co">     Clear lstm initial state or</span></span>
<span id="cb3-17"><a href="#cb3-17" aria-hidden="true" tabindex="-1"></a><span class="co">     set the state with a user-defined value.</span></span>
<span id="cb3-18"><a href="#cb3-18" aria-hidden="true" tabindex="-1"></a><span class="co">  */</span></span>
<span id="cb3-19"><a href="#cb3-19" aria-hidden="true" tabindex="-1"></a>  <span class="cf">if</span> <span class="op">(*</span>states<span class="op">)</span> <span class="op">{</span></span>
<span id="cb3-20"><a href="#cb3-20" aria-hidden="true" tabindex="-1"></a>    memset<span class="op">(*</span>states<span class="op">,</span> <span class="dv">0</span><span class="op">,</span> size_in_bytes<span class="op">);</span></span>
<span id="cb3-21"><a href="#cb3-21" aria-hidden="true" tabindex="-1"></a>  <span class="op">}</span></span>
<span id="cb3-22"><a href="#cb3-22" aria-hidden="true" tabindex="-1"></a>  _lstm_instance_idx<span class="op">++;</span></span>
<span id="cb3-23"><a href="#cb3-23" aria-hidden="true" tabindex="-1"></a><span class="op">}</span></span>
<span id="cb3-24"><a href="#cb3-24" aria-hidden="true" tabindex="-1"></a><span class="op">...</span></span>
<span id="cb3-25"><a href="#cb3-25" aria-hidden="true" tabindex="-1"></a><span class="dt">void</span> clear_lstm_states<span class="op">(</span><span class="dt">void</span><span class="op">)</span> <span class="op">{</span></span>
<span id="cb3-26"><a href="#cb3-26" aria-hidden="true" tabindex="-1"></a>    <span class="cf">for</span> <span class="op">(</span><span class="dt">int</span> i<span class="op">=</span><span class="dv">0</span><span class="op">;</span> i<span class="op">&lt;</span>NUM_INSTANCES<span class="op">;</span> i<span class="op">++)</span> <span class="op">{</span></span>
<span id="cb3-27"><a href="#cb3-27" aria-hidden="true" tabindex="-1"></a>            memset<span class="op">(</span>_lstm_states<span class="op">[</span>i<span class="op">],</span> <span class="dv">0</span><span class="op">,</span> _lstm_states_size<span class="op">[</span>i<span class="op">]);</span></span>
<span id="cb3-28"><a href="#cb3-28" aria-hidden="true" tabindex="-1"></a>    <span class="op">}</span></span>
<span id="cb3-29"><a href="#cb3-29" aria-hidden="true" tabindex="-1"></a><span class="op">}</span></span>
<span id="cb3-30"><a href="#cb3-30" aria-hidden="true" tabindex="-1"></a><span class="op">...</span></span>
<span id="cb3-31"><a href="#cb3-31" aria-hidden="true" tabindex="-1"></a>aiInit<span class="op">();</span></span>
<span id="cb3-32"><a href="#cb3-32" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-33"><a href="#cb3-33" aria-hidden="true" tabindex="-1"></a><span class="co">/* main processing loop */</span></span>
<span id="cb3-34"><a href="#cb3-34" aria-hidden="true" tabindex="-1"></a><span class="dt">int</span> sample_n <span class="op">=</span> <span class="dv">0</span><span class="op">;</span></span>
<span id="cb3-35"><a href="#cb3-35" aria-hidden="true" tabindex="-1"></a><span class="cf">while</span> <span class="op">(</span><span class="dv">1</span><span class="op">)</span> <span class="op">{</span></span>
<span id="cb3-36"><a href="#cb3-36" aria-hidden="true" tabindex="-1"></a>    <span class="co">/* 1 - Acquire, pre-process and fill the input buffers */</span></span>
<span id="cb3-37"><a href="#cb3-37" aria-hidden="true" tabindex="-1"></a>    acquire_and_process_data<span class="op">(</span>in_data<span class="op">);</span></span>
<span id="cb3-38"><a href="#cb3-38" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-39"><a href="#cb3-39" aria-hidden="true" tabindex="-1"></a>    <span class="co">/* 2 - Call inference engine */</span></span>
<span id="cb3-40"><a href="#cb3-40" aria-hidden="true" tabindex="-1"></a>    <span class="cf">if</span> <span class="op">(</span>sample_n<span class="op">++</span> <span class="op">&gt;</span> <span class="dv">20</span><span class="op">)</span> <span class="op">{</span></span>
<span id="cb3-41"><a href="#cb3-41" aria-hidden="true" tabindex="-1"></a>        clear_lstm_states<span class="op">();</span></span>
<span id="cb3-42"><a href="#cb3-42" aria-hidden="true" tabindex="-1"></a>        sample_n <span class="op">=</span> <span class="dv">0</span><span class="op">;</span></span>
<span id="cb3-43"><a href="#cb3-43" aria-hidden="true" tabindex="-1"></a>    <span class="op">}</span></span>
<span id="cb3-44"><a href="#cb3-44" aria-hidden="true" tabindex="-1"></a>    aiRun<span class="op">(</span>in_data<span class="op">,</span> out_data<span class="op">);</span></span>
<span id="cb3-45"><a href="#cb3-45" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb3-46"><a href="#cb3-46" aria-hidden="true" tabindex="-1"></a>    <span class="co">/* 3 - Post-process the predictions */</span></span>
<span id="cb3-47"><a href="#cb3-47" aria-hidden="true" tabindex="-1"></a>    post_process<span class="op">(</span>out_data<span class="op">);</span></span>
<span id="cb3-48"><a href="#cb3-48" aria-hidden="true" tabindex="-1"></a><span class="op">}</span></span></code></pre></div>
<p>To free the allocated resources, second weak function is also defined and called when the instance is destroyed (<a href="embedded_client_api.html#ref_api_create"><code>ai_&lt;network&gt;_destroy()</code></a> function).</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode c"><code class="sourceCode c"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>AI_DECLARE_WEAK</span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="dt">void</span> _deallocate_lstm_states<span class="op">(</span>ai_float <span class="op">**</span>states<span class="op">)</span></span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a><span class="op">{</span></span>
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a>  <span class="cf">if</span> <span class="op">(*</span>states<span class="op">)</span> <span class="op">{</span></span>
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a>    free<span class="op">(*</span>states<span class="op">);</span></span>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a>    <span class="op">*</span>states <span class="op">=</span> NULL<span class="op">;</span></span>
<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a>  <span class="op">}</span></span>
<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a><span class="op">}</span></span></code></pre></div>
</section>
<section id="validate-command-limitation" class="level1">
<h1>Validate command limitation</h1>
<p>With the current implementation of the <em>aiValidation</em> firmware, the state buffers are created and reset only during the initialization of the firmware. If multiple <a href="command_line_interface.html#ref_validate_cmd"><code>validate</code></a> command are used, the board should be re-start between two executions.</p>
<pre class="batch"><code># board should be reset.
$ stm32ai validate model.h5 --mode stm32 -b 20</code></pre>
<p>There is no limitation for the validation on desktop. Run-time is re-instantiated between two executions.</p>
<pre class="batch"><code>$ stm32ai validate model.h5 -b 20</code></pre>
<!-- External ST resources/links -->
<!-- Internal resources/links -->
<!-- External resources/links -->
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</section>
<section id="references" class="level1">
<h1>References</h1>
<table>
<colgroup>
<col style="width: 18%" />
<col style="width: 81%" />
</colgroup>
<thead>
<tr class="header">
<th style="text-align: left;">ref</th>
<th style="text-align: left;">description</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td style="text-align: left;">[DS]</td>
<td style="text-align: left;">X-CUBE-AI - <em>AI expansion pack for STM32CubeMX</em> <a href="https://www.st.com/en/embedded-software/x-cube-ai.html">https://www.st.com/en/embedded-software/x-cube-ai.html</a></td>
</tr>
<tr class="even">
<td style="text-align: left;">[UM]</td>
<td style="text-align: left;">User manual - Getting started with X-CUBE-AI Expansion Package for Artificial Intelligence (AI) <a href="https://www.st.com/resource/en/user_manual/dm00570145.pdf">(pdf)</a></td>
</tr>
<tr class="odd">
<td style="text-align: left;">[CLI]</td>
<td style="text-align: left;">stm32ai - Command Line Interface <a href="command_line_interface.html">(link)</a></td>
</tr>
<tr class="even">
<td style="text-align: left;">[API]</td>
<td style="text-align: left;">Embedded inference client API <a href="embedded_client_api.html">(link)</a></td>
</tr>
<tr class="odd">
<td style="text-align: left;">[METRIC]</td>
<td style="text-align: left;">Evaluation report and metrics <a href="evaluation_metrics.html">(link)</a></td>
</tr>
<tr class="even">
<td style="text-align: left;">[TFL]</td>
<td style="text-align: left;">TensorFlow Lite toolbox support <a href="supported_ops_tflite.html">(link)</a></td>
</tr>
<tr class="odd">
<td style="text-align: left;">[KERAS]</td>
<td style="text-align: left;">Keras toolbox support <a href="supported_ops_keras.html">(link)</a></td>
</tr>
<tr class="even">
<td style="text-align: left;">[ONNX]</td>
<td style="text-align: left;">ONNX toolbox support <a href="supported_ops_onnx.html">(link)</a></td>
</tr>
<tr class="odd">
<td style="text-align: left;">[FAQS]</td>
<td style="text-align: left;">FAQs <a href="faqs.html">(link)</a></td>
</tr>
<tr class="even">
<td style="text-align: left;">[QUANT]</td>
<td style="text-align: left;">Quantization and quantize command <a href="quantization.html">(link)</a></td>
</tr>
<tr class="odd">
<td style="text-align: left;">[RELOC]</td>
<td style="text-align: left;">Relocatable binary network support <a href="relocatable.html">(link)</a></td>
</tr>
<tr class="even">
<td style="text-align: left;">[CUST]</td>
<td style="text-align: left;">How to support the Keras Lambda/custom layers <a href="how_to_do_keras_lambda_custom.html">(link)</a></td>
</tr>
<tr class="odd">
<td style="text-align: left;">[TFLM]</td>
<td style="text-align: left;">TensorFlow Lite for Microcontroller support <a href="tflite_micro_support.html">(link)</a></td>
</tr>
<tr class="even">
<td style="text-align: left;">[INST]</td>
<td style="text-align: left;">Setting the environment <a href="setting_env.html">(link)</a></td>
</tr>
</tbody>
</table>
</section>
<section id="revision-history" class="level1">
<h1>Revision history</h1>
<table>
<thead>
<tr class="header">
<th style="text-align: left;">Date</th>
<th style="text-align: left;">version</th>
<th style="text-align: left;">changes</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td style="text-align: left;"><strong>2021-10-02</strong></td>
<td style="text-align: left;">r1.0</td>
<td style="text-align: left;">initial version</td>
</tr>
</tbody>
</table>
</section>



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	- <b> Keras stateful LSTM support </b>
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			<br> r1.0
		 - AI PLATFORM r7.0.0-dev
			 (Embedded Inference Client API 1.1.0) 
			 - Command Line Interface r1.4.2 
		
	
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